Many organizations collect large amounts of patient event data related to activities for treating a patient for various medical conditions. This patient event data can typically be complex and sparse in time with each event having multiple data attributes, and properties as well as nested sub levels. This complex medical data may come in a variety of forms and is often provided in an unstructured format. Due to the vast amount of complex medical data, current database systems lack the flexibility to effectively handle or assemble such data to provide reproductive or auditable analytics over time.